Máté Farkas

956 total citations · 1 hit paper
24 papers, 613 citations indexed

About

Máté Farkas is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Máté Farkas has authored 24 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Atomic and Molecular Physics, and Optics, 17 papers in Artificial Intelligence and 3 papers in Statistical and Nonlinear Physics. Recurrent topics in Máté Farkas's work include Quantum Mechanics and Applications (16 papers), Quantum Information and Cryptography (16 papers) and Quantum Computing Algorithms and Architecture (13 papers). Máté Farkas is often cited by papers focused on Quantum Mechanics and Applications (16 papers), Quantum Information and Cryptography (16 papers) and Quantum Computing Algorithms and Architecture (13 papers). Máté Farkas collaborates with scholars based in Spain, Poland and United Kingdom. Máté Farkas's co-authors include Jędrzej Kaniewski, P. Bernát Szabó, József Csóka, László Gyevi‐Nagy, Mihály Kállay, Ádám Ganyecz, Bence Ladóczki, Gyula Samu, Lóránt Szegedy and Péter R. Nagy and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and IEEE Transactions on Information Theory.

In The Last Decade

Máté Farkas

23 papers receiving 604 citations

Hit Papers

The MRCC program system: Accurate quantum chemistry from ... 2020 2026 2022 2024 2020 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The MRCC program system: Accurate quantum chemistry from water to proteins
    2020 366 citations Mihály Kállay, Péter R. Nagy et al. The Journal of Chemical Physics profile →

Peers

Máté Farkas
Tyler Y. Takeshita United States
Dmitry I. Lyakh United States
Bo Peng United States
Andrew G. Taube United States
Fabienne Goldfarb France
Emmanuel Giner France
Matthew R. Hermes United States
Sandra Eibenberger Austria
Ilya G. Ryabinkin Canada
Norm M. Tubman United States
Tyler Y. Takeshita United States
Máté Farkas
Citations per year, relative to Máté Farkas Máté Farkas (= 1×) peers Tyler Y. Takeshita

Countries citing papers authored by Máté Farkas

Since Specialization
Citations

This map shows the geographic impact of Máté Farkas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Máté Farkas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Máté Farkas more than expected).

Fields of papers citing papers by Máté Farkas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Máté Farkas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Máté Farkas. The network helps show where Máté Farkas may publish in the future.

Co-authorship network of co-authors of Máté Farkas

This figure shows the co-authorship network connecting the top 25 collaborators of Máté Farkas. A scholar is included among the top collaborators of Máté Farkas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Máté Farkas. Máté Farkas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Araújo, Mateus, et al.. (2025). Self-testing tilted strategies for maximal loophole-free nonlocality. npj Quantum Information. 11(1). 2 indexed citations
2.
Farkas, Máté, Nikolai Miklin, & Armin Tavakoli. (2025). Simple and general bounds on quantum random access codes. Quantum. 9. 1643–1643. 2 indexed citations
3.
Farkas, Máté. (2024). Unbounded Device-Independent Quantum Key Rates from Arbitrarily Small Nonlocality. Physical Review Letters. 132(21). 210803–210803. 6 indexed citations
4.
Farkas, Máté, et al.. (2024). Maximal intrinsic randomness of a quantum state. Physical review. A. 110(1). 1 indexed citations
5.
Farkas, Máté, et al.. (2023). Invertible Map between Bell Nonlocal and Contextuality Scenarios. Physical Review Letters. 131(22). 14 indexed citations
6.
Farkas, Máté, et al.. (2023). Upper bounds on key rates in device-independent quantum key distribution based on convex-combination attacks. Quantum. 7. 1199–1199. 5 indexed citations
7.
Farkas, Máté, Jędrzej Kaniewski, & Ashwin Nayak. (2023). Mutually Unbiased Measurements, Hadamard Matrices, and Superdense Coding. IEEE Transactions on Information Theory. 69(6). 3814–3824. 1 indexed citations
8.
Farkas, Máté, et al.. (2023). Characterizing and quantifying the incompatibility of quantum instruments. Physical review. A. 107(3). 8 indexed citations
9.
Farkas, Máté, et al.. (2022). Upper Bounds on Key Rates in Device-Independent Quantum Key Distribution Based on Convex-Combination Attacks. QTu4C.1–QTu4C.1. 2 indexed citations
10.
Farkas, Máté, et al.. (2022). Compatibility of quantum instruments. Physical review. A. 105(5). 9 indexed citations
11.
Farkas, Máté, et al.. (2021). Bell Nonlocality Is Not Sufficient for the Security of Standard Device-Independent Quantum Key Distribution Protocols. Physical Review Letters. 127(5). 50503–50503. 26 indexed citations
12.
Farkas, Máté, et al.. (2021). Characterising and bounding the set of quantum behaviours in contextuality scenarios. Quantum. 5. 484–484. 18 indexed citations
13.
14.
Farkas, Máté, et al.. (2020). Robust self-test of high-dimension mutually unbiased bases with commercial multi-core fiber. 96. 1–2. 1 indexed citations
15.
Kállay, Mihály, Péter R. Nagy, Dávid Mester, et al.. (2020). The MRCC program system: Accurate quantum chemistry from water to proteins. The Journal of Chemical Physics. 152(7). 74107–74107. 366 indexed citations breakdown →
16.
Tavakoli, Armin, Máté Farkas, Denis Rosset, Jean-Daniel Bancal, & Jędrzej Kaniewski. (2019). Mutually unbiased bases and symmetric informationally complete measurements in Bell experiments: Bell inequalities, device-independent certification and applications. arXiv (Cornell University). 5 indexed citations
17.
Farkas, Máté & Jędrzej Kaniewski. (2019). Self-testing mutually unbiased bases in the prepare-and-measure scenario. Physical review. A. 99(3). 56 indexed citations
18.
Designolle, Sébastien, Máté Farkas, & Jędrzej Kaniewski. (2019). Incompatibility robustness of quantum measurements: a unified framework. New Journal of Physics. 21(11). 113053–113053. 47 indexed citations
19.
Farkas, Máté, et al.. (2018). Az időjárási viszonyok hatása mézgás éger és kocsányos tölgy állományok növekedésére talajvízháztartás javítását célzó beavatkozások mellett. Üdvözöljük a Publicatio oldalán (University of West Hungary). 8(2). 9–16.
20.
Farkas, Máté, Daniel Martínez, Jaime Cariñe, et al.. (2018). Certifying an Irreducible 1024-Dimensional Photonic State Using Refined Dimension Witnesses. Physical Review Letters. 120(23). 230503–230503. 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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